


'''simple docstring'''


import unittest

from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


UpperCAmelCase_						:  List[Any]				  =						get_tests_dir('fixtures/test_sentencepiece.model')





@require_sentencepiece
@require_tokenizers
class        lowercase__    (		_snake_case	,	unittest.TestCase   ):





							'''simple docstring'''


							A_				: Any       =    XLNetTokenizer
							A_				: Optional[int]       =    XLNetTokenizerFast
							A_				: Dict       =    True
							A_				: Optional[Any]       =    True






							def UpperCAmelCase_      (       self    ):
											super().setUp()

											# We have a SentencePiece fixture for testing
											_SCREAMING_SNAKE_CASE					:			str							= XLNetTokenizer(__snake_case       ,   keep_accents=__snake_case    )
											tokenizer.sanitize_special_tokens()
											tokenizer.save_pretrained(self.tmpdirname    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE					:			Tuple							= """<s>"""
											_SCREAMING_SNAKE_CASE					:			Any							= 1

											self.assertEqual(self.get_tokenizer()._convert_token_to_id(__snake_case    )       ,   __snake_case    )
											self.assertEqual(self.get_tokenizer()._convert_id_to_token(__snake_case    )       ,   __snake_case    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE					:			Tuple							= list(self.get_tokenizer().get_vocab().keys()    )

											self.assertEqual(vocab_keys[0]       ,   """<unk>"""    )
											self.assertEqual(vocab_keys[1]       ,   """<s>"""    )
											self.assertEqual(vocab_keys[-1]       ,   """<eod>"""    )
											self.assertEqual(len(__snake_case    )       ,   1006    )






							def UpperCAmelCase_      (       self    ):
											self.assertEqual(self.get_tokenizer().vocab_size       ,   1000    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE					:			int							= XLNetTokenizer(__snake_case       ,   keep_accents=__snake_case    )

											_SCREAMING_SNAKE_CASE					:			str							= tokenizer.tokenize("""This is a test"""    )
											self.assertListEqual(__snake_case       ,   ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]    )

											self.assertListEqual(tokenizer.convert_tokens_to_ids(__snake_case    )       ,   [285, 46, 10, 170, 382]    )

											_SCREAMING_SNAKE_CASE					:			Optional[int]							= tokenizer.tokenize("""I was born in 92000, and this is falsé."""    )
											self.assertListEqual(
											    __snake_case       ,   [
											        SPIECE_UNDERLINE + """I""",
											        SPIECE_UNDERLINE + """was""",
											        SPIECE_UNDERLINE + """b""",
											        """or""",
											        """n""",
											        SPIECE_UNDERLINE + """in""",
											        SPIECE_UNDERLINE + """""",
											        """9""",
											        """2""",
											        """0""",
											        """0""",
											        """0""",
											        """,""",
											        SPIECE_UNDERLINE + """and""",
											        SPIECE_UNDERLINE + """this""",
											        SPIECE_UNDERLINE + """is""",
											        SPIECE_UNDERLINE + """f""",
											        """al""",
											        """s""",
											        """é""",
											        """.""",
											    ]       ,   )
											_SCREAMING_SNAKE_CASE					:			Tuple							= tokenizer.convert_tokens_to_ids(__snake_case    )
											self.assertListEqual(__snake_case       ,   [8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]    )

											_SCREAMING_SNAKE_CASE					:			Optional[int]							= tokenizer.convert_ids_to_tokens(__snake_case    )
											self.assertListEqual(
											    __snake_case       ,   [
											        SPIECE_UNDERLINE + """I""",
											        SPIECE_UNDERLINE + """was""",
											        SPIECE_UNDERLINE + """b""",
											        """or""",
											        """n""",
											        SPIECE_UNDERLINE + """in""",
											        SPIECE_UNDERLINE + """""",
											        """<unk>""",
											        """2""",
											        """0""",
											        """0""",
											        """0""",
											        """,""",
											        SPIECE_UNDERLINE + """and""",
											        SPIECE_UNDERLINE + """this""",
											        SPIECE_UNDERLINE + """is""",
											        SPIECE_UNDERLINE + """f""",
											        """al""",
											        """s""",
											        """<unk>""",
											        """.""",
											    ]       ,   )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE					:			Tuple							= XLNetTokenizer(__snake_case       ,   do_lower_case=__snake_case    )
											_SCREAMING_SNAKE_CASE					:			Dict							= tokenizer.tokenize("""I was born in 92000, and this is falsé."""    )
											self.assertListEqual(
											    __snake_case       ,   [
											        SPIECE_UNDERLINE + """""",
											        """i""",
											        SPIECE_UNDERLINE + """was""",
											        SPIECE_UNDERLINE + """b""",
											        """or""",
											        """n""",
											        SPIECE_UNDERLINE + """in""",
											        SPIECE_UNDERLINE + """""",
											        """9""",
											        """2""",
											        """0""",
											        """0""",
											        """0""",
											        """,""",
											        SPIECE_UNDERLINE + """and""",
											        SPIECE_UNDERLINE + """this""",
											        SPIECE_UNDERLINE + """is""",
											        SPIECE_UNDERLINE + """f""",
											        """al""",
											        """se""",
											        """.""",
											    ]       ,   )
											self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""    )       ,   ["""▁he""", """ll""", """o"""]    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE					:			Tuple							= XLNetTokenizer(__snake_case       ,   do_lower_case=__snake_case    )
											_SCREAMING_SNAKE_CASE					:			Optional[int]							= tokenizer.tokenize("""I was born in 92000, and this is falsé."""    )
											self.assertListEqual(
											    __snake_case       ,   [
											        SPIECE_UNDERLINE + """I""",
											        SPIECE_UNDERLINE + """was""",
											        SPIECE_UNDERLINE + """b""",
											        """or""",
											        """n""",
											        SPIECE_UNDERLINE + """in""",
											        SPIECE_UNDERLINE + """""",
											        """9""",
											        """2""",
											        """0""",
											        """0""",
											        """0""",
											        """,""",
											        SPIECE_UNDERLINE + """and""",
											        SPIECE_UNDERLINE + """this""",
											        SPIECE_UNDERLINE + """is""",
											        SPIECE_UNDERLINE + """f""",
											        """al""",
											        """se""",
											        """.""",
											    ]       ,   )






							@slow
							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= XLNetTokenizer.from_pretrained("""xlnet-base-cased"""    )

											_SCREAMING_SNAKE_CASE					:			Optional[int]							= tokenizer.encode("""sequence builders"""       ,   add_special_tokens=__snake_case    )
											_SCREAMING_SNAKE_CASE					:			Optional[int]							= tokenizer.encode("""multi-sequence build"""       ,   add_special_tokens=__snake_case    )

											_SCREAMING_SNAKE_CASE					:			int							= tokenizer.build_inputs_with_special_tokens(__snake_case    )
											_SCREAMING_SNAKE_CASE					:			int							= tokenizer.build_inputs_with_special_tokens(__snake_case       ,   __snake_case    )

											assert encoded_sentence == text + [4, 3]
											assert encoded_pair == text + [4] + text_a + [4, 3]






							@slow
							def UpperCAmelCase_      (       self    ):
											# fmt: off
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= {"""input_ids""": [[17, 2_1442, 270, 17, 10, 1_4645, 318, 34, 17, 4546, 3145, 787, 13, 7752, 2_2018, 23, 21, 17, 4546, 3145, 787, 13, 3352, 1_4431, 13, 5500, 11, 1176, 580, 13, 1_6819, 4797, 23, 17, 10, 1_7135, 658, 19, 457, 7932, 13, 184, 19, 3154, 1_7135, 6468, 19, 1404, 1_2269, 19, 4229, 5356, 1_6264, 46, 19, 17, 2_0545, 1_0395, 9, 9, 9, 11, 28, 6421, 9531, 2_0729, 17, 10, 353, 1_7022, 11, 21, 6421, 9531, 1_6949, 17, 10, 1_1509, 753, 11, 33, 95, 2421, 7385, 956, 1_4431, 2626, 25, 842, 7385, 4836, 21, 1429, 2272, 9855, 3120, 161, 2_4738, 19, 1_3203, 658, 218, 787, 21, 430, 1_8482, 847, 2637, 9, 4, 3], [5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 322, 2_2178, 27, 1064, 22, 956, 13, 1_1101, 1429, 5854, 2_4313, 1_8953, 40, 422, 2_4366, 68, 1758, 37, 1_0483, 1_4257, 31, 207, 263, 21, 203, 3773, 25, 71, 9735, 9, 4, 3], [5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 32, 2049, 3442, 17, 1_3894, 3380, 23, 95, 18, 1_7634, 2288, 9, 4, 3]], """token_type_ids""": [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2], [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2], [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
											# fmt: on

											self.tokenizer_integration_test_util(
											    expected_encoding=__snake_case       ,   model_name="""xlnet-base-cased"""       ,   revision="""c841166438c31ec7ca9a106dee7bb312b73ae511"""       ,   )








'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCAmelCase_						:  Dict				  =						{
    'configuration_mobilebert': [
        'MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'MobileBertConfig',
        'MobileBertOnnxConfig',
    ],
    'tokenization_mobilebert': ['MobileBertTokenizer'],
}

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase_						:  Optional[Any]				  =						['MobileBertTokenizerFast']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase_						:  Optional[Any]				  =						[
				    'MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'MobileBertForMaskedLM',
				    'MobileBertForMultipleChoice',
				    'MobileBertForNextSentencePrediction',
				    'MobileBertForPreTraining',
				    'MobileBertForQuestionAnswering',
				    'MobileBertForSequenceClassification',
				    'MobileBertForTokenClassification',
				    'MobileBertLayer',
				    'MobileBertModel',
				    'MobileBertPreTrainedModel',
				    'load_tf_weights_in_mobilebert',
				]

try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase_						:  List[str]				  =						[
				    'TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'TFMobileBertForMaskedLM',
				    'TFMobileBertForMultipleChoice',
				    'TFMobileBertForNextSentencePrediction',
				    'TFMobileBertForPreTraining',
				    'TFMobileBertForQuestionAnswering',
				    'TFMobileBertForSequenceClassification',
				    'TFMobileBertForTokenClassification',
				    'TFMobileBertMainLayer',
				    'TFMobileBertModel',
				    'TFMobileBertPreTrainedModel',
				]


if TYPE_CHECKING:
				from .configuration_mobilebert import (
				    MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    MobileBertConfig,
				    MobileBertOnnxConfig,
				)
				from .tokenization_mobilebert import MobileBertTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_mobilebert_fast import MobileBertTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_mobilebert import (
								    MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    MobileBertForMaskedLM,
								    MobileBertForMultipleChoice,
								    MobileBertForNextSentencePrediction,
								    MobileBertForPreTraining,
								    MobileBertForQuestionAnswering,
								    MobileBertForSequenceClassification,
								    MobileBertForTokenClassification,
								    MobileBertLayer,
								    MobileBertModel,
								    MobileBertPreTrainedModel,
								    load_tf_weights_in_mobilebert,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_mobilebert import (
								    TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    TFMobileBertForMaskedLM,
								    TFMobileBertForMultipleChoice,
								    TFMobileBertForNextSentencePrediction,
								    TFMobileBertForPreTraining,
								    TFMobileBertForQuestionAnswering,
								    TFMobileBertForSequenceClassification,
								    TFMobileBertForTokenClassification,
								    TFMobileBertMainLayer,
								    TFMobileBertModel,
								    TFMobileBertPreTrainedModel,
								)

else:
				import sys

				UpperCAmelCase_						:  str				  =						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




